Personal Health Metrics Data Management Using Symmetric 5G Data Channels

Abstract

The integrated collection of personal health data represents a relevant research topic, which is enhanced further by the development of next-generation mobile networks that can be used in order to transport the acquired medical data. The gathering of personal health data has become recently feasible using relevant wearable personal devices. Nevertheless, these devices do not possess sufficient computational power, and do not offer proper local data storage capabilities. This paper presents an integrated personal health metrics data management system, which considers a virtualized symmetric 5G data transportation system. The personal health data are acquired using a client application component, which is normally deployed on the user’s mobile device, regardless it is a smartphone, smartwatch, or another kind of personal mobile device. The collected data are securely transported to the cloud data processing components, using a virtualized 5G infrastructure and homomorphically encrypted data packages. The system has been comprehensively assessed through the consideration of a real-world use case, which is presented.

An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors

“…As an example, the authors of this paper designed and implemented an integrated personal health data management system, which uses both hardware [ 205 ] and software sensors, to collect data about the physiological parameters that are monitored [ 206 ]. Full data privacy is ensured through homomorphic encryption routines, which were illustrated by the authors of [ 73 , 74 ]. The initial incorrect implementation of certain homomorphic encryption routines determined the triggering of false health warnings in the case of individuals who were not suffering from the particular medical conditions.…”

“…Moreover, it is important to mention the contributions that were described in [ 73 , 74 ], considering that they presented one of the few existing integrated personal data management systems, which fully implements data protection mechanisms considering all the relevant stages: data collection, transportation, processing, and long-term storage.…”

“…Our thorough literature review proves that although interesting contributions are described in the literature, most of the existing algorithmic and functional models miss some of the mandatory technical features. In contrast, he integrated medical data management system described in [ 74 ] represents one of the few approaches that fulfills all of the necessary algorithmic and technical constraints.…”

“…Additionally, existing scientific studies report integrated mHealth and eHealth software systems that support the collection of personal health data using mobile and wearable devices, the processing of the data components, the format of the encrypted data to conduct arithmetic operations, and secure-long term personal health data storage. This type of full privacy preserving approach, which relates to homomorphic encryption and virtualized 5G data channels, was described in [ 73 , 74 ].…”